Efficacy and safety of first-line checkpoint inhibitors-based treatments for non-oncogene-addicted non-small-cell lung cancer: a systematic review and meta-analysis.

BACKGROUND: Frontline immune checkpoint inhibitors (ICI)-based regimens in non-oncogene-addicted non-small-cell lung cancer (NSCLC) have been deeply investigated. To rank the available therapeutic options, we carried out a systematic review and Bayesian meta-analysis. METHODS: A comprehensive search for randomized controlled trials (RCTs) of ICI regimens, and a pairwise and a network meta-analysis (NMA) with an all-comers and a stratified strategy were conducted. Endpoints were overall survival (OS), progression-free survival (PFS), objective response rate (ORR) and treatment-related adverse events (TRAEs). RESULTS: Nineteen RCTs involving 17 treatment regimens were included. For the all-comers population, pembrolizumab/chemotherapy (CT) and cemiplimab were most likely the best treatments. For programmed death-ligand 1 (PD-L1) <1% nivolumab/ipilimumab with/without CT, for PD-L1 >1% and 1%-49% pembrolizumab/CT and for PD-L1 >50% cemiplimab ranked first for OS. In non-squamous (NSQ), pembrolizumab with/without CT ranked first for OS; cemiplimab ranked worse than the unselected population. In squamous (SQ), pooled hazard ratio (HR) showed a better chance in improving efficacy for combination strategy, while monotherapy did not, except for cemiplimab that ranked second. Atezolizumab/CT/bevacizumab ranked first in most subgroups for PFS. Direct comparison showed a non-statistically significant benefit of ICI regimens for the liver metastases cohort in OS, with a good ranking for pembrolizumab/CT and atezolizumab/bevacizumab/CT. Regarding brain metastases, all ICI regimens demonstrated an improvement in OS and PFS compared to CT. Nivolumab/ipilimumab/CT ranked better in this subset. CONCLUSIONS: Our meta-analysis updated on the most recent findings demonstrates that different ICI treatments rank differently in specific NSCLC settings (histology, biomarker and clinical presentation) offering a novel challenging scenario for clinical decision making and research planning.

A gene expression inflammatory signature specifically predicts multiple myeloma evolution and patients survival.

Multiple myeloma (MM) is closely dependent on cross-talk between malignant plasma cells and cellular components of the inflammatory/immunosuppressive bone marrow milieu, which promotes disease progression, drug resistance, neo-angiogenesis, bone destruction and immune-impairment. We investigated the relevance of inflammatory genes in predicting disease evolution and patient survival. A bioinformatics study by Ingenuity Pathway Analysis on gene expression profiling dataset of monoclonal gammopathy of undetermined significance, smoldering and symptomatic-MM, identified inflammatory and cytokine/chemokine pathways as the most progressively affected during disease evolution. We then selected 20 candidate genes involved in B-cell inflammation and we investigated their role in predicting clinical outcome, through univariate and multivariate analyses (log-rank test, logistic regression and Cox-regression model). We defined an 8-genes signature (IL8, IL10, IL17A, CCL3, CCL5, VEGFA, EBI3 and NOS2) identifying each condition (MGUS/smoldering/symptomatic-MM) with 84% accuracy. Moreover, six genes (IFNG, IL2, LTA, CCL2, VEGFA, CCL3) were found independently correlated with patients' survival. Patients whose MM cells expressed high levels of Th1 cytokines (IFNG/LTA/IL2/CCL2) and low levels of CCL3 and VEGFA, experienced the longest survival. On these six genes, we built a prognostic risk score that was validated in three additional independent datasets. In this study, we provide proof-of-concept that inflammation has a critical role in MM patient progression and survival. The inflammatory-gene prognostic signature validated in different datasets clearly indicates novel opportunities for personalized anti-MM treatment.